Towards a Model for Inferring Trust in Heterogeneous Social Networks

Akhoondi, Masoud; Habibi, Jafar; Sayyadi, Mohsen

doi:10.1109/ams.2008.167

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…This trust model was used in distributed systems, but it could not predict the trust of users in social network. In [23], a genetic algorithm-based approach to inferring trust was introduced. The approach used heterogeneous relations for inferring trust.…”

Section: Related Workmentioning

confidence: 99%

A Fuzzy System for Evaluating Trustworthiness of Users in a Social Network

SHAFIEI¹,

Shirgahi²,

Barzegar³

2022

IIUMEJ

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In recent years, the emergence of various web-based social networks has led to the growth of social network users. These networks have become popular as a medium for disseminating information and communication. Governments and organizations also use social networks as a platform for better services. However, acting in such networks depends on the level of trust that members have with each other. The combination of personality attributes of a person can create a mental impression of the amount of trust that a person has. This amount of trust can affect the person's future interactions. Therefore, trust is an essential and important matter in these networks, especially when someone interacts with someone else on a web-based social network. We discuss this issue in this paper and provide a method for evaluating it. Measuring the accuracy is not easy for the users who are interacting with the social network. Here, the interactions are virtual. In this paper, we have used fuzzy logic to apply ambiguous data and to evaluate trustworthiness by taking into account the various personality attributes of users such as reliability, availability, interest, patience, and adaptability. As we used these attributes as input to the fuzzy system and based on the relevant fuzzy rules, we evaluated the trustworthiness of users in social networks. The proposed fuzzy system is extendable, because in this system, trust can be defined as a set of one or more personality attributes. Epinions social network dataset is also used to simulate and validate the proposed approach. In the proposed method, the MAE value is less than 0.015 and F-Score value more than 0.86. Based on the results, the presented fuzzy system shows an acceptable accuracy for evaluating the trustworthiness of users. ABSTRAK: Sejak beberapa tahun kebelakangan ini, kemunculan pelbagai rangkaian web sosial telah menyebabkan pertumbuhan pengguna rangkaian sosial. Rangkaian ini telah menjadi popular sebagai medium penularan informasi dan komunikasi. Kerajaan dan organisasi juga menggunakan rangkaian sosial sebagai platfom bagi menyediakan servis perkhidmatan terbaik. Namun, pemakaian rangkaian ini bergantung kepada kepercayaan pengguna antara sesama pengguna. Gabungan ciri-ciri personaliti terhadap seseorang menyebabkan terciptanya persepsi secara mental pada kepercayaan ke atas seseorang. Jumlah kepercayaan ini akan memberi kesan terhadap interaksi yang akan berlaku pada masa depan ke atas individu tersebut. Oleh itu, kepercayaan sangat penting dalam rangkaian ini, terutama apabila seseorang berinteraksi dengan mereka di jaringan sosial web. Isu ini dibincangkan dalam kajian ini dan kaedah evaluasi turut dihuraikan. Mengukur ketepatan pengguna dalam jaringan sosial tidak mudah. Di sini, interaksi berlaku secara maya. Kajian ini menggunakan logik kabur pada data tidak jelas dan bagi mengukur tahap kepercayaan, pelbagai ciri personaliti individu diukur, seperti kebolehpercayaan, kebolehdapatan, minat, kesabaran dan kebolehsesuian. Ciri-ciri tersebut digunakan sebagai input kepada sistem rawak dan berdasarkan peraturan rawak, tahap kebolehpercayaan pengguna diukur dalam rangkaian sosial. Sistem rawak yang dicadangkan ini boleh dilanjutkan, kerana dalam sistem ini kepercayaan boleh dimaksudkan sebagai satu set atau lebih ciri-ciri personaliti. Anggapan pada set data rangkaian sosial turut digunakan bagi simulasi dan pengesahan kaedah yang dicadangkan. Bagi kaedah yang dicadangkan ini, nilai MAE adalah kurang daripada 0.015 dan nilai skor-F lebih daripada 0.86. Berdasarkan dapatan kajian ini, sistem rawak yang dikaji ini menunjukkan ketepatan yang boleh diterima bagi mengukur tahap kebolehpercayaan pengguna.

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Section: Related Workmentioning

confidence: 99%

A Fuzzy System for Evaluating Trustworthiness of Users in a Social Network

SHAFIEI¹,

Shirgahi²,

Barzegar³

2022

IIUMEJ

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“…For sociologists, trust is social relationship between members in a society. This notion has been the basis of trust in multi agent systems where the developers have exploited the similarities between a multi agent system and a group of people interacting with each other (Gan, He, & Ding, 2009;Akhoondi, Habibi, & Sayyadi, 2008). When people interact with each other, they develop trust between actors based on the outcome of the transactions.…”

Section: Trust and Trust Computingmentioning

confidence: 99%

Statistically Enhanced Multi-Dimensional Trust Computing Mechanism for Cloud Computing

Firdhous

Hassan

Ghazali

2013

International Journal of Mobile Computing and Multimedia Communications

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Quality of service plays an important role in distributed systems. Cloud computing has been the recent entrant to the distributed system market and has revolutionized computing by changing the way computing resources are accessed and paid for. Users can access cloud services and pay only for the usage similar to utilities. Trust computing systems can be employed for identifying the service providers quality in terms of their adherence to the committed in SLAs. Several trust computing mechanisms have been proposed in literature based on various algorithms and functions. Almost all of them are based on a single performance parameter and modify the trust scores monotonously when performance deviations are reported. This paper proposes a trust computing mechanism that statistically validates the attribute monitored before modifying the trust scores. Hence the proposed mechanism is protected from momentary fluctuations in system performances. The experiments conducted show that the trust scores computed using the proposed mechanism are more representative of the long term system performance than the ones that were computed without the validation of the inputs.

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“…Sociologists approach to trust as a social relationship between people. Social context of trust has been commonly employed in multi agent systems and social networks [7,[13][14]. The similarity between multi agent system and a social network are exploited in these works as agents and people behave in a similar fashion interacting with, gathering information from and modeling each other for developing trust in each other.…”

Section: Trust and Trust Managementmentioning

confidence: 99%

Trust Management in Cloud Computing: A Critical Review

Firdhous

Ghazali

Hassan

2012

Int J on Adv. in ICT for Emerging Countries

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Abstract-Cloud computing has been attracting the attention of several researchers both in the academia and the industry as it provides many opportunities for organizations by offering a range of computing services. For cloud computing to become widely adopted by both the enterprises and individuals, several issues have to be solved. A key issue that needs special attention is security of clouds, and trust management is an important component of cloud security.In this paper, the authors look at what trust is and how trust has been applied in distributed computing. Trust models proposed for various distributed system has then been summarized. The trust management systems proposed for cloud computing have been investigated with special emphasis on their capability, applicability in practical heterogonous cloud environment and implementabilty. Finally, the proposed models/systems have been compared with each other based on a selected set of cloud computing parameters in a table.

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Towards a Model for Inferring Trust in Heterogeneous Social Networks

Cited by 6 publications

References 15 publications

A Fuzzy System for Evaluating Trustworthiness of Users in a Social Network

A Fuzzy System for Evaluating Trustworthiness of Users in a Social Network

Statistically Enhanced Multi-Dimensional Trust Computing Mechanism for Cloud Computing

Trust Management in Cloud Computing: A Critical Review

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